Backed by our AI and Machine Learning on Microsoft Azure specialization, we help global brands and enterprises translate AI’s potential into practical business solutions. Below are inspiring examples of how we’ve solved real-life problems with AI and machine learning (ML), building solutions that enhance daily operations and strategic decisions-making.
A global CPG company struggled to scale a limited Excel-based solution that cannot handle large-scale trade panel data. They also lacked a reliable tool to optimize pricing across multiple markets. Gaps in understanding price elasticities left their product managers unable to predict the impact of pricing and promotional strategies.
Lingaro created an interactive dashboard that streamlined the comparison of their products with competitors. The dashboard also included a simulation tool for “what-if” scenarios. This provided insights into the impact of different pricing strategies on sales, profits, and potential risks to their other products across various categories and channels. To ensure the dashboard’s accessibility and adoption, Lingaro’s revenue growth management (RGM) experts conducted hands-on training sessions and provided detailed guides during user acceptance testing.
The company has since adopted this AI-powered dashboard as the go-to source for pricing strategies in four markets, with plans to expand to two more. It provides a comprehensive view of products ready for price adjustments. It also helps users understand the impact and risks of new pricing and promotional strategies on the brand. Through a series of knowledge transfer sessions, we also brought their IT department up to speed with the latest in MLOps practices in Azure Machine Learning. This markedly improved the synergy and cross-functional collaboration between their technology and business teams.
A leading multinational beverage corporation wanted to pinpoint the most promising retail outlets, organize the right marketing activities, fine-tune visit frequencies, and curate the right product assortment.
They partnered with Lingaro to upgrade and scale up an existing ML PoC and deploy it across more than 20 markets. The tool’s code was refactored to enable its users across their marketing, route-to-market (RtM), and sales departments to optimize sales and profit.
Lingaro’s ML solution now equips their teams with detailed insights into sales potential and volume for every outlet and product category. RtM teams can now strategically allocate their efforts, focusing on outlets with the greatest potential and scaling back on those with less promise. By using historical data, microsegmentation, and profitability analysis, the tool provides recommendations on the ideal product mix and quantities. This data-driven guidance not only improved sales, but also enhanced cost efficiency.
A Fortune 100 beverage company partnered with Lingaro to improve retail operations and refine marketing efforts globally, achieving the focused effectiveness of a single outlet. This would be done using an ML-powered optimization tool that had been piloted in one country. They aimed at transforming this prototype into a working solution across 28 markets.
Lingaro turned this proof of concept (PoC) into a commercial solution, updating the code to handle a wide range of data, features, and standards. We delivered seven key components, writing over 300,000 lines of code. Our work combined and refined data from various sources to create a unified, versatile model that meets specific business requirements. By applying best practices in DataOps, MLOps, and ModelOps, we sped up the implementation, improved the usability of the ML models, and addressed complex technical challenges. The diverse team consisted of 60 experts in areas like AI engineering, DevOps, and project management.
The solution was rolled out in just six months, cutting data platform costs by 50% and reducing processing time by 40%. Additionally, we implemented 164 change requests to accommodate the evolving demands of their business. With the commercialized AI tool, they can now ensure that each retail channel operates at peak performance — from forecasting demand, managing inventory efficiently, personalizing marketing efforts, and enhancing the overall customer experience. Its deployment across different markets also enabled them to do this consistently worldwide.
As our case studies show, AI is becoming a dependable tool to tackle challenges in retail and CPG, from streamlining marketing activities and addressing evolving consumer preferences to optimizing operations. However, success in adopting AI requires a robust foundation in data and ensuring its readiness to adopt and adapt to AI.
In a 2023 survey by Microsoft and IDC, 71% of global business leaders reported that their organizations are already using AI. However, they face significant obstacles in adopting and scaling AI. Backed by our AI and Machine Learning on Microsoft Azure specialization, Lingaro can help global brands and enterprises overcome these hurdles. Lingaro’s experts are recognized for their capability to blend technical knowledge with business strategy to ensure ROI in AI. Additionally, Lingaro’s data science and AI practice provides AI accelerators, MLOps frameworks, and other AI toolkits that enhance the speed, scale, and security of AI projects, which also help optimize costs. Lingaro’s access to partnerships and resources extend to our clients, adding a layer of assurance and pathway to cutting-edge solutions and support.
Today, Lingaro helps leading companies across consumer goods, manufacturing, retail, luxury, and life sciences realize the full value of their data — from strategy, development, and operations to adoption.